A comprehensive digital concierge providing deep local insights for living, working, and visiting Madrid.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install madrid
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install madrid using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Madrid?
The Madrid skill is a specialized knowledge module designed to empower AI agents with deep, localized intelligence about Spain's capital. It moves beyond generic travel advice by providing structured data for multiple personas, including tourists, tech professionals, students, and entrepreneurs. By leveraging this skill within the Openclaw Skills ecosystem, users can access hyper-relevant information regarding the tech industry, startup culture, and specific neighborhood dynamics.
The skill is built to handle the complexities of relocating or visiting, offering granular details on everything from the nuances of 'siesta culture' to specific salary benchmarks for senior software engineers. It serves as a practical bridge between raw data and actionable local wisdom, ensuring that AI-driven interactions regarding Madrid are both accurate and contextually aware.
Madrid Use Cases
- Planning optimized 1, 3, or 7-day visitor itineraries with a focus on local gems over tourist traps.
- Navigating the Madrid tech scene and researching salary expectations for engineering roles.
- Evaluating neighborhoods based on lifestyle profiles like 'Young Professional', 'Family', or 'Budget-conscious'.
- Budgeting for relocation by analyzing current rent, transit, and student living costs.
- Understanding seasonal weather extremes to plan optimal travel or moving windows.
How Madrid Works
- The AI agent first identifies the user context to determine if they are a visitor, resident, tech worker, or student.
- The system references the
neighborhoods-index.mdor other specific category files to fetch relevant metadata. - It applies core rules regarding safety, climate, and transit to ensure recommendations are realistic and safe.
- The skill cross-references user preferences with neighborhood profiles to provide a curated list of 'Best Areas'.
- It filters out common local traps and suggests authentic alternatives based on the integrated local services data.
Madrid Setup
To deploy the Madrid skill, ensure your agent environment is configured to read local markdown-based knowledge sets.
# Clone the skill into your agent's skills directory
git clone https://github.com/openclaw/skill-madrid.git ./skills/madrid
# Ensure the directory structure is preserved for file-based lookups
ls ./skills/madrid/*.md
No external binaries are required, as the skill operates on a comprehensive collection of Markdown data files compatible with any Openclaw Skills implementation.
Madrid Data Schema & Taxonomy
The skill utilizes a modular file structure to organize its extensive local knowledge base:
| Data Category | Filename Pattern | Information Type |
|---|---|---|
| Tourism | visitor-*.md |
Attractions, lodging, and itineraries |
| Districts | neighborhoods-*.md |
Detailed area comparisons and choosing guides |
| Gastronomy | food-*.md |
Traditional cuisine, markets, and dietary tips |
| Economic | cost.md, tech.md, startup.md |
Salaries, rent, and industry insights |
| Logistics | transport.md, safety.md, climate.md |
Infrastructure and environmental data |
Madrid Advanced Features
- Profile-specific neighborhood matching for demographics ranging from entrepreneurs to families.
- Real-time transit cost analysis including multi-card discounts and fixed-rate airport connections.
- 'Tourist Trap' avoidance logic that redirects users from overpriced venues to authentic local alternatives.
- Tech industry salary benchmarking for senior-level roles and startup ecosystem mapping.
- Seasonal packing and logistics guidance based on continental climate extremes.
SKILL.md
Loading
Related Openclaw Skills
Madeira
A comprehensive digital companion for navigating Madeira as a visitor, digital nomad, or prospective resident.
macOS
A technical guide for mastering macOS system administration, command-line nuances, and automation workflows.
Los Angeles
A comprehensive intelligence layer for navigating Los Angeles as a visitor, resident, or professional.
Loop
A controlled autonomous iteration engine that executes agent tasks repeatedly until specific success criteria are met.
A high-performance email management skill utilizing the himalaya CLI and macOS SQLite for secure, platform-optimized mail operations.
Malay Language Naturalizer
A specialized skill designed to generate natural, human-sounding Malay text that avoids the robotic formality of standard AI.
Featured*
